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Jamie D. Riggs - Handbook for Applied Modeling: Non-Gaussian and Correlated Data - 9781316601051 - V9781316601051
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Handbook for Applied Modeling: Non-Gaussian and Correlated Data

€ 49.78
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Description for Handbook for Applied Modeling: Non-Gaussian and Correlated Data paperback. This compact, entry-level Handbook equips applied practitioners to choose and use core models for real-world data - with R and SAS. Num Pages: 350 pages. BIC Classification: PBT. Dimension: 253 x 177. .
Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing ... Read more

Product Details

Publisher
Cambridge University Press
Format
Paperback
Publication date
2017
Condition
New
Weight
28g
Number of Pages
228
Place of Publication
Cambridge, United Kingdom
ISBN
9781316601051
SKU
V9781316601051
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-1

About Jamie D. Riggs
Jamie D. Riggs is an adjunct lecturer in the Predictive Analytics program at Northwestern University, Illinois. She specializes in the statistical issues of solar system cratering processes, solar physics, and galactic dynamics, and has collaborated with researchers at the Los Alamos National Laboratory, New Mexico and the Southwest Research Institute, Texas. She has held technical and managerial positions at Sun ... Read more

Reviews for Handbook for Applied Modeling: Non-Gaussian and Correlated Data
'This book is a guide to modeling and analyzing non-Gaussian and correlated data. There is clearly a need for such a book to help less experienced data scientists ... The data sets and models are well explained, and the limitations of each type of model on the various data sets is illustrated by frequent plots.' Peter Rabinovitch, MAA Reviews 'This ... Read more

Goodreads reviews for Handbook for Applied Modeling: Non-Gaussian and Correlated Data


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